As to a gamut of color reproduction (Hereinafter, it is called “gamut”) representing an image signal (defined by standard of broadcast wave), its range is narrower than a color range of natural recognized by the naked eye of human. For example, a gamut represented in digital broadcast is defined by ITU-R BT.709. This gamut is a limited range in visible light. Briefly, if a subject has a color outside the gamut of BT.709, color information of the subject (captured as the image) is compressed within the gamut of ITU-R BT.709, and a broadcast wave having compressed color information is generated.
On the other hand, recently, by development of a color image display device, a gamut of the device is widening. For example, the display device using an organic EL or a wide gamut LCD is spreading. As to the LCD, by improvement of a light source or a color filter, its color purity can be heightened. Alternatively, by increasing a primary color of color LED (used for backlight of LCD), wider gamut can be realized. In these display devices, a color having wider range than ITU-R BT.709 can be represented.
When a broadcast wave is displayed on the display device having wider range, if an image signal of the broadcast wave is displayed with fidelity, a merit to display in the wide gamut is lost. Furthermore, when the gamut of ITU-R BT.709 is expanded to a gamut reproduced by the display device, the subject is unnaturally displayed with clear color different from its original color.
Accordingly, technique to estimate an original color of the subject from the image signal having compressed gamut and to restore the original color is necessary. As to pixels having saturated color over a prescribed gamut, each signal value (RGB) of the pixels is often compressed as the maximum (255). In this case, a method for estimating original signal values (not saturated) of the pixels using a dichromatic reflection model is proposed. For example, this method is disclosed in “Color Restoration From Saturated Images—Restoration method up to 2 channel saturations—” Takanori TAMAKI, Toshikazu WADA, Kazumasa SUZUKI (Wakayama University), IEICE Technical Report, vol. 108, no. 484, PRMU2008-243, pp. 19-24, March 2009 . . . reference 1.
However, after capturing an image of the subject, in process to compress a gamut of the image, various transforms are executed to the image. The various transforms include not only clipping of pixel value (having saturated gamut as mentioned above) but also gamut mapping or transform by tone-curve. The input image signal does not have information representing which transform was executed to the image. Accordingly, restoration of the original color of the image is difficult.
Briefly, in above-mentioned conventional technique, after capturing an image of the subject, a gamut lost in process to compress the image cannot be correctly restored.